Optimized Deep Brain Stimulation for Epileptic Encephalopathies

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In the UK, 600,000 patients have epilepsy. For 30% of these patients, seizures are not controlled by available anti-seizure medication. The rate of refractory cases can be higher for genetic epilepsies, with 60% of SYNGAP1-associated absence seizures cases remaining resistant to drug treatment. The SYNGAP1 gene encodes a powerful regulator of neuronal synaptic connectivity. SYNGAP1 pathogenic mutations are an important predictor of neurodevelopmental disorders, intellectual disability, and epilepsy. Another important predictor are mutations in the SCN2A gene. SCN2A encodes voltage-gated sodium channels critical for actional potential generation and propagation. Drug resistance for SCN2A-associated epilepsy is also around 60%. Both SYNGAP1 and SCN2A disorder are classified as an epileptic encephalopathy, in which cognitive and behavioural deficits are thought to worsen with uncontrolled seizures. Therefore, there is a critical need to develop novel therapeutic strategies that block seizures in patients. Electrical stimulation within the brain, or deep brain stimulation (DBS), is an approved treatment for intractable epilepsies. Nonetheless, it has not been tested in genetic epilepsies or to treat absence seizures. Furthermore, DBS could be significantly optimized as stimulation parameters such as the strength, frequency and duration of each electrical pulse are often chosen without clear rationale. In the main clinical trial leading to DBS approval for epilepsy, there was a 56% reduction in median seizures, although only 6 of 81 patients achieved total seizure freedom. Thus, DBS could potentially stop seizures in epileptic encephalopathies such as SYNGAP1 and SCN2A disorders, and stimulation parameters may be identifiable for maximum efficacy. To test this, new rat models can be utilised, including a model of SYNGAP1 disorder in which the critical GAP domain of the gene is deleted and a SCN2A heterozygous knockout model. Animals heterozygous for the deletion (Syngap+/A-GAP) demonstrate cognitive, social, and sleep abnormalities, as well as decreased connectivity between EEG electrodes and a high rate of spontaneous absence seizures. Preliminary investigation indicates that SCN2A heterozygous animals (Scn2a+/-) also demonstrate high rates of spontaneous absence seizures, and there will be further investigation into the behavioural and seizure phenotypes of this model. This project will determine whether deep brain stimulation (DBS) with optimised stimulation parameters can block seizures in rat models of epileptic encephalopathy and test whether improved DBS could benefit patients. Optimised DBS parameters to block absence seizures will be determined from EEG and multi-site recordings from genetic epilepsy rodent models such as Syngap+/A-GAP and Scn2a+/- rats. The recordings available in the Gonzalez-Sulser lab, from thalamo-cortical circuits thought to mediate absence seizures, will be analysed, and algorithms developed to estimate a low-dimensional representation of brain functional connectivity around seizure onset, which in combination with machine learning and network control theory, will be utilized to explore the stimulation parameter space. Using the optimised parameters identified, DBS will be performed in the rat models of epileptic encephalopathy to determine whether DBS can block absence seizures and examine its clinical potential. Then, EEG stimulation parameters will be validated in human EEG. We will determine whether absence seizures in SYNGAP1 patient EEG data, available in the Zuberi lab, display similar activity dynamics as Syngap+/A-GAP rats and, whether optimized stimulation parameters could be utilized in patients. We aim that SCN2A patient EEG data will be similarly evaluated.